Reducing Potentially Inappropriate Prescriptions for Older Patients Using Computerized Decision Support Tools: Systematic Review

Deprescribing interventions in older adults: An overview of systematic reviews

OBJECTIVE

The growing deprescribing field is challenged by a lack of consensus around evidence and knowledge gaps. The objective of this overview of systematic reviews was to summarize the review evidence for deprescribing interventions in older adults.

METHODS

11 databases were searched from 1st January 2005 to 16th March 2023 to identify systematic reviews. We summarized and synthesized the results in two steps. Step 1 summarized results reported by the included reviews (including meta-analyses). Step 2 involved a narrative synthesis of review results by outcome. Outcomes included medication-related outcomes (e.g., medication reduction, medication appropriateness) or twelve other outcomes (e.g., mortality, adverse events). We summarized outcomes according to subgroups (patient characteristics, intervention type and setting) when direct comparisons were available within the reviews. The quality of included reviews was assessed using A MeaSurement Tool to Assess systematic Reviews 2 (AMSTAR 2).

RESULTS

We retrieved 3,228 unique citations and assessed 135 full-text articles for eligibility. Forty-eight reviews (encompassing 17 meta-analyses) were included. Thirty-one of the 48 reviews had a general deprescribing focus, 16 focused on specific medication classes or therapeutic categories and one included both. Twelve of 17 reviews meta-analyzed medication-related outcomes (33 outcomes: 25 favored the intervention, 7 found no difference, 1 favored the comparison). The narrative synthesis indicated that most interventions resulted in some evidence of medication reduction while for other outcomes we found primarily no evidence of an effect. Results were mixed for adverse events and few reviews reported adverse drug withdrawal events. Limited information was available for people with dementia, frailty and multimorbidity. All but one review scored low or critically low on quality assessment.

CONCLUSION

Deprescribing interventions likely resulted in medication reduction but evidence on other outcomes, in particular relating to adverse events, or in vulnerable subgroups or settings was limited. Future research should focus on designing studies powered to examine harms, patient-reported outcomes, and effects on vulnerable subgroups.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020178860.

Deprescribing: An umbrella review

This umbrella review examined systematic reviews of deprescribing studies by characteristics of intervention, population, medicine, and setting. Clinical and humanistic outcomes, barriers and facilitators, and tools for deprescribing are presented. The Medline database was used. The search was limited to systematic reviews and meta-analyses published in English up to April 2022. Reviews reporting deprescribing were included, while those where depre-scribing was not planned and supervised by a healthcare professional were excluded. A total of 94 systematic reviews (23 meta--analyses) were included. Most explored clinical or humanistic outcomes (70/94, 74 %); less explored attitudes, facilitators, or barriers to deprescribing (17/94, 18 %); few focused on tools (8/94, 8.5 %). Reviews assessing clinical or humanistic outcomes were divided into two groups: reviews with deprescribing intervention trials (39/70, 56 %; 16 reviewing specific deprescribing interventions and 23 broad medication optimisation interventions), and reviews with medication cessation trials (31/70, 44 %). Deprescribing was feasible and resulted in a reduction of inappropriate medications in reviews with deprescribing intervention trials. Complex broad medication optimisation interventions were shown to reduce hospitalisation, falls, and mortality rates. In reviews of medication cessation trials, a higher frequency of adverse drug withdrawal events underscores the importance of prioritizing patient safety and exercising caution when stopping medicines, particularly in patients with clear and appropriate indications.

Deintensification of potentially inappropriate medications amongst older frail people with type 2 diabetes: Protocol for a cluster randomised controlled trial (D-MED study)

AIMS

Amongst elderly people with type 2 diabetes (T2D) over prescribing can result in emergency ambulance call-outs, falls and fractures and increased mortality, particularly in frail patients. Current clinical guidelines, however, remain focused on medication intensification rather than deintensification where appropriate. This study aims to evaluate the effectiveness of an electronic decision-support system and training for the deintensification of potentially inappropriate medications amongst older frail people with T2D, when compared to 'usual' care at 12-months.

METHODS

This study is an open-label, multi-site, two-armed pragmatic cluster-randomised trial. GP practices randomised to the 'enhanced care' group have an electronic decision support system installed and receive training on the tool and de-intensification of diabetes medications. The system flags eligible patients for possible deintensification of diabetes medications, linking the health care professional to a clinical algorithm. The primary outcome will be the number of patients at 12-months who have had potentially inappropriate diabetes medications de-intensified.

RESULTS

Study recruitment commenced in June 2022. Data collection commenced in January 2023. Baseline data have been extracted from 40 practices (3145 patients).

CONCLUSIONS

Digital technology, involving computer decision systems, may have the potential to reduce inappropriate medications and aid the process of de-intensification.

TRIAL REGISTRATION

International Standard Randomised Controlled Trial Number: ISRCTN53221378. Available at: https://www.isrctn.com/ISRCTN53221378.

Clinician and Family Caregiver Perspectives on Deprescribing Chronic Disease Medications in Older Nursing Home Residents Near the End of Life

INTRODUCTION

Nursing home (NH) residents with limited life expectancy (LLE) who are intensely treated for hyperlipidemia, hypertension, or diabetes may benefit from deprescribing.

OBJECTIVE

This study sought to describe NH clinician and family caregiver perspectives on key influences on deprescribing decisions for chronic disease medications in NH residents near the end of life.

METHODS

We recruited family caregivers of veterans who recently died in a Veterans Affairs (VA) NH, known as community living centers (CLCs), and CLC healthcare clinicians (physicians, nurse practitioners, physician assistants, pharmacists, registered nurses). Respondents completed semi-structured interviews about their experiences with deprescribing statin, antihypertensive, and antidiabetic medications for residents near end of life. We conducted thematic analysis of interview transcripts to identify key themes regarding influences on deprescribing decisions.

RESULTS

Thirteen family caregivers and 13 clinicians completed interviews. Key themes included (1) clinicians and caregivers both prefer to minimize drug burden; (2) clinical factors strongly influence deprescribing of chronic disease medications, with differences in how clinicians and caregivers weigh specific factors; (3) caregivers trust and rely on clinicians to make deprescribing decisions; (4) clinicians perceive caregiver involvement and buy-in as essential to deprescribing decisions, which requires time and effort to obtain; and (5) clinicians perceive conflicting care from other clinicians as a barrier to deprescribing.

CONCLUSIONS

Findings suggest a need for efforts to encourage communication with and education for family caregivers of residents with LLE about deprescribing, and to foster better collaboration among clinicians in CLC and non-CLC settings.

Implementation considerations of deprescribing interventions: A scoping review

Over half of older adults experience polypharmacy, including medications that may be inappropriate or unnecessary. Deprescribing, which is the process of discontinuing or reducing inappropriate and/or unnecessary medications, is an effective way to reduce polypharmacy. This review summarizes (1) the process of deprescribing and conceptual models and tools that have been developed to facilitate deprescribing, (2) barriers, enablers, and factors associated with deprescribing, and (3) characteristics of deprescribing interventions in completed trials, as well as (4) implementation considerations for deprescribing in routine practice. In conceptual models of deprescribing, multilevel factors of the patient, clinician, and health-care system are all related to the efficacy of deprescribing. Numerous tools have been developed for clinicians to facilitate deprescribing, yet most require substantial time and, thus, may be difficult to implement during routine health-care encounters. Multiple deprescribing interventions have been evaluated, which mostly include one or more of the following components: patient education, medication review, identification of deprescribing targets, and patient and/or provider communication about high-risk medications. Yet, there has been limited consideration of implementation factors in prior deprescribing interventions, especially with regard to the personnel and resources in existing health-care systems and the feasibility of incorporating components of deprescribing interventions into the routine care processes of clinicians. Future trials require a more balanced consideration of both effectiveness and implementation when designing deprescribing interventions.

A mixed methods analysis of the medication review intervention centered around the use of the 'Systematic Tool to Reduce Inappropriate Prescribing' Assistant (STRIPA) in Swiss primary care practices

BACKGROUND

Electronic clinical decision support systems (eCDSS), such as the 'Systematic Tool to Reduce Inappropriate Prescribing' Assistant (STRIPA), have become promising tools for assisting general practitioners (GPs) with conducting medication reviews in older adults. Little is known about how GPs perceive eCDSS-assisted recommendations for pharmacotherapy optimization. The aim of this study was to explore the implementation of a medication review intervention centered around STRIPA in the 'Optimising PharmacoTherapy In the multimorbid elderly in primary CAre' (OPTICA) trial.

METHODS

We used an explanatory mixed methods design combining quantitative and qualitative data. First, quantitative data about the acceptance and implementation of eCDSS-generated recommendations from GPs (n = 21) and their patients (n = 160) in the OPTICA intervention group were collected. Then, semi-structured qualitative interviews were conducted with GPs from the OPTICA intervention group (n = 8), and interview data were analyzed through thematic analysis.

RESULTS

In quantitative findings, GPs reported averages of 13 min spent per patient preparing the eCDSS, 10 min performing medication reviews, and 5 min discussing prescribing recommendations with patients. On average, out of the mean generated 3.7 recommendations (SD=1.8). One recommendation to stop or start a medication was reported to be implemented per patient in the intervention group (SD=1.2). Overall, GPs found the STRIPA useful and acceptable. They particularly appreciated its ability to generate recommendations based on large amounts of patient information. During qualitative interviews, GPs reported the main reasons for limited implementation of STRIPA were related to problems with data sourcing (e.g., incomplete data imports), preparation of the eCDSS (e.g., time expenditure for updating and adapting information), its functionality (e.g., technical problems downloading PDF recommendation reports), and appropriateness of recommendations.

CONCLUSIONS

Qualitative findings help explain the relatively low implementation of recommendations demonstrated by quantitative findings, but also show GPs' overall acceptance of STRIPA. Our results provide crucial insights for adapting STRIPA to make it more suitable for regular use in future primary care settings (e.g., necessity to improve data imports).

TRIAL REGISTRATION

Clinicaltrials.gov NCT03724539, date of first registration: 29/10/2018.

Polypharmacy and Deprescribing in Older Adults

Older adults commonly end up on many medications. Deprescribing is an important part of individualizing care for older adults. It is an opportunity to discuss treatment options and revisit medications that may not have been reassessed in many years. A large evidence base exists in the field, suggesting that deprescribing is feasible and safe, though questions remain about the potential clinical benefits. Deprescribing research faces a myriad of challenges, such as identifying and employing the optimal outcome measures. Further, there is uncertainty about which deprescribing approaches are likely to be most effective and in what contexts. Evidence on barriers and facilitators to deprescribing has underscored how deprescribing in routine clinical practice can be complex and challenging. Thus, finding practical, sustainable ways to implement deprescribing is a priority for future research in the field.

Antihypertensive treatment in people of very old age with frailty: time for a paradigm shift?

The optimal management of hypertension in individuals aged 80 years or older with frailty remains uncertain due to multiple gaps in evidence. Complex health issues, polypharmacy, and limited physiological reserve make responding to antihypertensive treatments unpredictable. Patients in this age group may have limited life expectancy, so their quality of life should be prioritized when making treatment decisions. Further research is needed to identify which patients would benefit from more relaxed blood pressure targets and which antihypertensive medications are preferable or should be avoided. A paradigm shift is required in attitudes towards treatment, placing equal emphasis on deprescribing and prescribing when optimizing care. This review discusses the current evidence on managing hypertension in individuals aged 80 years or older with frailty, but further research is essential to address the gaps in knowledge and improve the care of this population.

Development and validation of PolyScan, an information technology triage tool for older adults with polypharmacy: a healthcare informatics study

Introduction Polypharmacy is associated with potentially inappropriate medicine prescribing and avoidable medicine-related harm. Polypharmacy should not be perceived as inherently harmful. Instead, priority should be placed on reducing inappropriate prescribing. Aim The study aimed to develop and validate PolyScan, a primary care information technology tool, to triage older adults with polypharmacy who are prescribed potentially inappropriate medicines. Methods Twenty-one indicators from a New Zealand criteria of potentially inappropriate medicines to correct for older adults with polypharmacy were developed into a set of implementable definitions. The definitions were applied as algorithmic logic statements used to interrogate hospital and emergency department records and pharmaceutical collection data to classify whether each indicator was present at an individual patient level, and then triage individuals based on the number of indicators met. Validity was evaluated by comparing PolyScan's accuracy against a manual review of healthcare records for 300 older adults. Results PolyScan was successfully implemented as a tool that can be used to identify potentially inappropriate prescribing in older adults with polypharmacy at different levels of aggregation. The tool has utility for individual practitioners delivering patient care, primary care organisations undertaking quality improvement programmes, and policymakers considering system-level interventions for medicines-related safety. During the validity assessment, PolyScan identified nine individuals (3%) with polypharmacy and indicators of potentially inappropriate medicine. Five unique indicators were detected. PolyScan achieved 100% sensitivity, specificity, and positive and negative predictive values. Discussion PolyScan can support clinicians, clinics, and policymakers with allocation of resources, rational medicine campaigns, and identifying individuals prescribed potentially inappropriate medicines for review.

Practice of pharmaceutical services and prescription analysis in internet-based psychiatric hospitals during COVID-19 pandemic in Wuxi, China

Objective

To study the practice of pharmaceutical services in internet-based psychiatric hospitals, and to analyze the prescriptions to ensure the safety and efficacy of internet-based medication in Wuxi, China.

Methods

All 1,259 internet-based prescriptions from our hospital in 2022 were collected, and data on patients' age, gender, diagnosis, medications used, medication types, dosage forms, rationality of medication use, and reasons for irrationality were analyzed through descriptive statistics.

Results

In the electronic prescriptions of internet-based psychiatric hospitals, females accounted for the majority (64.50%), with a female-to-male ratio of 1.82:1. Middle-aged and young adults accounted for the majority of patients (57.50%). There were 47 diagnosed diseases involved, with 89 types of medications used and 1,938prescriptions issued. Among them, there were 78 types of western medicine with 1,876 prescriptions (96.80%), and 11 types of traditional Chinese medicine with 62 prescriptions (3.20%). The main medications used were anti-anxiety and antidepressant medications (44.94%) and psychiatric medications (42.21%). The dosage forms were all oral, with tablets (78.53%), capsules (17.54%), and solution preparations (2.17%) being the top three in frequency. According to the prescription review results, the initial pass rate of internet-based system review was 64.26%. After intervention by the internet-based system and manual review by pharmacist reviewers, the final pass rate of internet-based prescriptions reached 99.76%.

Conclusion

The practice of pharmaceutical services and prescription analysis in internet-based psychiatric hospitals could significantly improve medication rationality, which fills the research gap in this field. In addition, it promotes the transformation of pharmaceutical service models.

Development of REDCap-based architecture for a clinical decision support tool linked to the electronic health record for assessment of medication appropriateness

Objective

To develop the architecture for a clinical decision support system (CDSS) linked to the electronic health record (EHR) using the tools provided by Research Electronic Data Capture (REDCap) to assess medication appropriateness in older adults with polypharmacy.

Materials and Methods

The tools available in REDCap were used to create the architecture for replicating a previously developed stand-alone system while overcoming its limitations.

Results

The architecture consists of data input forms, drug- and disease-mapper, rules engine, and report generator. The input forms integrate medication and health condition data from the EHR with patient assessment data. The rules engine evaluates medication appropriateness through rules built through a series of drop-down menus. The rules generate output, which are a set of recommendations to the clinician.

Discussion and conclusion

This architecture successfully replicates the stand-alone CDSS while addressing its limitations. It is compatible with several EHRs, easily shared among the large community using REDCap, and readily modifiable.

Impact of a Comprehensive Intervention Bundle Including the Drug Burden Index on Deprescribing Anticholinergic and Sedative Drugs in Older Acute Inpatients: A Non-randomised Controlled Before-and-After Pilot Study

INTRODUCTION

Implementation of the Drug Burden Index (DBI) as a risk assessment tool in clinical practice may facilitate deprescribing.

OBJECTIVE

The purpose of this study is to evaluate how a comprehensive intervention bundle using the DBI impacts (i) the proportion of older inpatients with at least one DBI-contributing medication stopped or dose reduced on discharge, compared with admission; and (ii) the changes in deprescribing of different DBI-contributing medication classes during hospitalisation.

METHODS

This before-and-after study was conducted in an Australian metropolitan tertiary referral hospital. Patients aged ≥ 75 years admitted to the acute aged care service for ≥ 48 h from December 2020 to October 2021 and prescribed DBI-contributing medication were included. During the control period, usual care was provided. During the intervention, access to the intervention bundle was added, including a clinician interface displaying DBI score in the electronic medical record. In a subsequent 'stewardship' period, a stewardship pharmacist used the bundle to provide clinicians with patient-specific recommendations on deprescribing of DBI-contributing medications.

RESULTS

Overall, 457 hospitalisations were included. The proportion of patients with at least one DBI-contributing medication stopped/reduced on discharge increased from 29.9% (control period) to 37.5% [intervention; adjusted risk difference (aRD) 6.5%, 95% confidence intervals (CI) -3.2 to 17.5%] and 43.1% (stewardship; aRD 12.1%, 95% CI 1.0-24.0%). The proportion of opioid prescriptions stopped/reduced rose from 17.9% during control to 45.7% during stewardship (p = 0.04).

CONCLUSION

Integrating a comprehensive intervention bundle and accompanying stewardship program is a promising strategy to facilitate deprescribing of sedative and anticholinergic medications in older inpatients.

Perspectives on Why Patients with Mild Cognitive Impairment Might Receive Fewer Cardiovascular Disease Treatments than Patients with Normal Cognition

BACKGROUND

People with mild cognitive impairment (MCI) receive fewer guideline-concordant treatments for cardiovascular disease (CVD) than people with normal cognition (NC).

OBJECTIVE

To understand physician perspectives on why patients with MCI receive fewer CVD treatments than patients with NC.

METHODS

As part of a mixed-methods study assessing how patient MCI influences physicians' decision making for acute myocardial infarction (AMI) and stroke treatments, we conducted a qualitative study using interviews of physicians. Topics included participants' reactions to data that physicians recommend fewer CVD treatments to patients with MCI and reasons why participants think fewer CVD treatments may be recommended to this patient population.

RESULTS

Participants included 22 physicians (8 cardiologists, 7 neurologists, and 7 primary care physicians). Most found undertreatment of CVD in patients with MCI unreasonable, while some participants thought it could be considered reasonable. Participants postulated that other physicians might hold beliefs that could be reasons for undertreating CVD in patients with MCI. These beliefs fell into four main categories: 1) patients with MCI have worse prognoses than NC, 2) patients with MCI are at higher risk of treatment complications, 3) patients' cognitive impairment might hinder their ability to consent or adhere to treatment, and 4) patients with MCI benefit less from treatments than NC.

CONCLUSION

These findings suggest that most physicians do not think it is reasonable to recommend less CVD treatment to patients with MCI than to patients with NC. Improving physician understanding of MCI might help diminish disparities in CVD treatment among patients with MCI.

Use of the consolidated framework for implementation research in a mixed methods evaluation of the EQUIPPED medication safety program in four academic health system emergency departments

Background

Enhancing Quality of Prescribing Practices for Older Adults Discharged from the Emergency Department (EQUIPPED) is an effective quality improvement program initially designed in the Veterans Administration (VA) health care system to reduce potentially inappropriate medication prescribing for adults aged 65 years and older. This study examined factors that influence implementation of EQUIPPED in EDs from four distinct, non-VA academic health systems using a convergent mixed methods design that operationalized the Consolidated Framework for Implementation Research (CFIR). Fidelity of delivery served as the primary implementation outcome.

Materials and methods

Four EDs implemented EQUIPPED sequentially from 2017 to 2021. Using program records, we scored each ED on a 12-point fidelity index calculated by adding the scores (1-3) for each of four components of the EQUIPPED program: provider receipt of didactic education, one-on-one academic detailing, monthly provider feedback reports, and use of order sets. We comparatively analyzed qualitative data from focus groups with each of the four implementation teams (n = 22) and data from CFIR-based surveys of ED providers (108/234, response rate of 46.2%) to identify CFIR constructs that distinguished EDs with higher vs. lower levels of implementation.

Results

Overall, three sites demonstrated higher levels of implementation (scoring 8-9 of 12) and one ED exhibited a lower level (scoring 5 of 12). Two constructs distinguished between levels of implementation as measured through both quantitative and qualitative approaches: patient needs and resources, and organizational culture. Implementation climate distinguished level of implementation in the qualitative analysis only. Networks and communication, and leadership engagement distinguished level of implementation in the quantitative analysis only.

Discussion

Using CFIR, we demonstrate how a range of factors influence a critical implementation outcome and build an evidence-based approach on how to prime an organizational setting, such as an academic health system ED, for successful implementation.

Conclusion

This study provides insights into implementation of evidence-informed programs targeting medication safety in ED settings and serves as a potential model for how to integrate theory-based qualitative and quantitative methods in implementation studies.

A systematic review defining non-beneficial and inappropriate end-of-life treatment in patients with non-cancer diagnoses: theoretical development for multi-stakeholder intervention design in acute care settings

Background

Non-beneficial treatment is closely tied to inappropriate treatment at the end-of-life. Understanding the interplay between how and why these situations arise in acute care settings according to the various stakeholders is pivotal to informing decision-making and best practice at end-of-life.

Aim

To define and understand determinants of  non-beneficial and inappropriate treatments for patients with a non-cancer diagnosis, in acute care settings at the end-of-life.

Design

Systematic review of peer-reviewed studies focusing on the above and conducted in upper-middle- and high-income countries. A narrative synthesis was undertaken, guided by Realist principles.

Data sources

Cochrane; PubMed; Scopus; Embase; CINAHL; and Web of Science.

Results

Sixty-six studies (32 qualitative, 28 quantitative, and 6 mixed-methods) were included after screening 4,754 papers. Non-beneficial treatment was largely defined as when the burden of treatment outweighs any benefit to the patient. Inappropriate treatment at the end-of-life was similar to this, but additionally accounted for patient and family preferences.

Contexts in which outcomes related to non-beneficial treatment and/or inappropriate treatment occurred were described as veiled by uncertainty, driven by organizational culture, and limited by profiles and characteristics of involved stakeholders. Mechanisms relating to ‘Motivation to Address Conflict & Seek Agreement’ helped to lessen uncertainty around decision-making. Establishing agreement was reliant on ‘Valuing Clear Communication and Sharing of Information’. Reaching consensus was dependent on ‘Choices around Timing & Documenting of end-of-life Decisions’.

Conclusion

A framework mapping determinants of non-beneficial and inappropriate end-of-life treatment is developed and proposed to be potentially transferable to diverse contexts. Future studies should test and update the framework as an implementation tool.

Trial registration

PROSPERO Protocol CRD42021214137.

LESS-PHARMA Study: Identifying and Deprescribing Potentially Inappropriate Medication in the Elderly Population with Excessive Polypharmacy in Primary Care

Potentially inappropriate medication (PIM) increases adverse drug reactions and mortality, especially in excessively polymedicated patients. General practitioners are often in charge of this process. Some tools have been created to support them in this matter. This study aimed to measure the amount of potentially inappropriate medication among excessively polymedicated patients using several supporting tools and assess the feasibility of these tools in primary care. Several explicit deprescribing criteria were used to identify potentially inappropriate medications. The level of agreement between all the criteria and the acceptance by the general practitioner (GP) was also measured. We analysed whether the drugs proposed for deprescribing were eventually withdrawn after twelve months. The total number of drugs prescribed was 2038. Six hundred and forty-nine drugs (31.8%) were considered potentially inappropriate by at least one of the tools. GPs agreed with the tools in 56.7% of the cases. In a 12-month period, 109 drugs, representing 29.6% of the drugs that GPs agreed to deprescribe, were withdrawn. Elderly excessively polymedicated patients accumulated a great number of PIMs. The use of deprescribing supporting tools, such as explicit criteria, is feasible in primary care, and these tools are well accepted by the GPs. However, eventual withdrawal was carried out in less than half of the cases.

Effectiveness of the MULTIPAP Plus intervention in youngest-old patients with multimorbidity and polypharmacy aimed at improving prescribing practices in primary care: study protocol of a cluster randomized trial

Background

The progressive ageing of the population is leading to an increase in multimorbidity and polypharmacy, which in turn may increase the risk of hospitalization and mortality. The enhancement of care with information and communications technology (ICT) can facilitate the use of prescription evaluation tools and support system for decision-making (DSS) with the potential of optimizing the healthcare delivery process.

Objective

To assess the effectiveness and cost-effectiveness of the complex intervention MULTIPAP Plus, compared to usual care, in improving prescriptions for young-old patients (65-74 years old) with multimorbidity and polypharmacy in primary care.

Methods/design

This is a pragmatic cluster-randomized clinical trial with a follow-up of 18 months in health centres of the Spanish National Health System. Unit of randomization: family physician. Unit of analysis: patient.

Population

Patients aged 65–74 years with multimorbidity (≥ 3 chronic diseases) and polypharmacy (≥ 5 drugs) during the previous 3 months were included.

Sample size

n = 1148 patients (574 per study arm).

Intervention

Complex intervention based on the ARIADNE principles with three components: (1) family physician (FP) training, (2) FP-patient interview, and (3) decision-making support system.

Outcomes

The primary outcome is a composite endpoint of hospital admission or death during the observation period measured as a binary outcome, and the secondary outcomes are number of hospital admission, all-cause mortality, use of health services, quality of life (EQ-5D-5L), functionality (WHODAS), falls, hip fractures, prescriptions and adherence to treatment. Clinical and sociodemographic factors will be explanatory variables.

Statistical analysis

The main result is the difference in percentages in the final composite endpoint variable at 18 months, with its corresponding 95% CI. Adjustments by the main confounding and prognostic factors will be performed through a multilevel analysis. All analyses will be carried out in accordance to the intention-to-treat principle.

Discussion

It is important to prevent the cascade of negative health and health care impacts attributable to the multimorbidity-polypharmacy binomial. ICT-enhanced routine clinical practice could improve the prescription process in patient care.

Trial registration

ClinicalTrials.gov NCT04147130. Registered on 22 October 2019

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06293-x.

Healthcare Costs Associated with Potentially Inappropriate Medication Prescribing Detected by Computer Algorithm Among Older Patients

INTRODUCTION

Potentially inappropriate medication prescribing (PIP) among older patients is associated with an increased risk of adverse events and hospitalization, and sometimes increased healthcare costs.

OBJECTIVE

The aim of this study was to explore the association between healthcare costs and PIP exposure among older patients.

METHODS

Analyses were conducted using data from the Multidomain Alzheimer Preventive Trial (MAPT). A computer algorithm was constructed to detect PIP based on various different explicit criteria-based tools, and the results were expressed in number of medication-related potential non-compliances (MRNCs). A prescription was considered potentially inappropriate if there were one or more MRNCs. We performed a cost analysis from the French National Health Insurance perspective, and also performed a multivariate analysis to identify the association between healthcare costs and PIP (number of MRNCs).

RESULTS

The computer algorithm analyzed medication prescribing from included patients (N = 1525 aged 75.3 ± 4.4 years; 64% women [n = 978]). PIP was associated with increased total healthcare costs and non-medication healthcare costs after adjusting for potential confounders. We also noted that healthcare costs tended to increase with the number of MRNCs. The mean additional healthcare costs were €517, €921, and €1669 per patient and year for patients with one or two MRNCs, three or four MRNCs, and five or more MRNCs, respectively, in comparison with patients with appropriate medication prescriptions.

CONCLUSION

These observations led us to conclude that interventions focused on reducing PIP could result in savings.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT00672685.

Decision-support systems for managing polypharmacy in the elderly: A scoping review

Polypharmacy, the consuming of more than five drugs, is a public health problem. It can lead to many interactions and adverse drug reactions and is very expensive. Therapeutic guidelines for managing polypharmacy in the elderly have been issued, but are highly complex, limiting their use. Decision-support systems have therefore been developed to automate the execution of these guidelines, or to provide information about drugs adapted to the context of polypharmacy. These systems differ widely in terms of their technical design, knowledge sources and evaluation methods. We present here a scoping review of electronic systems for supporting the management, by healthcare providers, of polypharmacy in elderly patients. Most existing reviews have focused mainly on evaluation results, whereas the present review also describes the technical design of these systems and the methodologies for developing and evaluating them. A systematic bibliographic search identified 19 systems differing considerably in terms of their technical design (rule-based systems, documentary approach, mixed); outputs (textual report, alerts and/or visual approaches); and evaluations (impact on clinical practices, impact on patient outcomes, efficiency and/or user satisfaction). The evaluations performed are minimal (among all the systems identified, only one system has been evaluated according to all the criteria mentioned above) and no machine learning systems and/or conflict management systems were retrieved. This review highlights the need to develop new methodologies, combining various approaches for decision support system in polypharmacy.

Cost Outcomes of Potentially Inappropriate Prescribing (PIP) in Middle-Aged Adults: A Delphi consensus and Cross-sectional Study

BACKGROUND

Potentially inappropriate prescribing (PIP) is common in older adults and is associated with increased medication costs and costs of associated adverse drug events (ADE). PIP also affects almost one-fifth of middle-aged adults (45-64 years old), as defined by the PRescribing Optimally in Middle-aged People's Treatments (PROMPT) criteria. However, there has been little research on PIP medication costs within this age group.

AIMS

Calculate the medication costs of PIP for middle-aged adults according to the 22 PROMPT criteria and compare with the cost of consensus-validated, evidence-based ('adequate') alternative prescribing scenarios.

METHODOLOGY

Adequate alternatives to the 22 PROMPT criteria were created via literature review. A Delphi consensus panel of experts were recruited (n=16), supported by a patient and public involvement group, to achieve consensus on the alternatives. A retrospective repeated cross-sectional study from 2014 to 2019 was then conducted utilising pseudonymised primary care data from Lambeth DataNet in South London (41 general practices, N=1,185,335, using LDN May 2020 extract) to calculate the cost of PIP.

RESULTS

The cross-sectional study included 55,880 patients. The total PIP cost was £2.79 million, with adequate alternative prescribing costing £2.74 million (cost savings of £51,278). Duplicate drug classes was the most costly criterion for both PIP and alternative prescribing.

CONCLUSIONS

This study calculated the medication costs of PIP and created alternative prescribing scenarios for the 22 PROMPT criteria. There is no substantial cost difference between adequate prescribing versus PIP. Future studies should investigate the wider health economic costs of alternative prescribing, such as reducing hospital admissions.

Introduction of an Ambulatory Care Medication Reconciliation Service in Dialysis Patients: Positive Impact on Medication Prescribing and Economic Benefit

OBJECTIVE

The aim of the study was to assess the implementation of medication reconciliation (MedRec) and medication-related costs in dialysis-dependent patients.

METHODS

Completed best possible medication history and reconciliation forms were collected within 6 months from 77 patients' file at the dialysis center. Outcome measures were number and types of medication discrepancies, medication-related problems (MRPs), and their potential to cause harm, in addition to the type and number of interventions conducted during MedRec and the resulted medication costs reduction.

RESULTS

The mean number of medications was 11 ± 4, which was reduced to 8 ± 3 (P < 0.0001) after MedRec. Medication discrepancies accounted for 55, and MRPs were raised by pharmacists 216 times, and 55% had the potential to cause moderate patient discomfort. Mediations were held in 1.2%, discontinued in 21.2%, and changed in 5.4%, which led to €75.665 (U.S. $85.33) and €459.93 (U.S. $511.979) reduction in medication costs per patient for 1 and 6 months, respectively.

CONCLUSIONS

Several discrepancies and MRPs were identified in the present study that put patients undergoing dialysis at risk for potential harm and adverse drug events. Regularly performing ambulatory MedRec and involving pharmacists in the model of care can improve the quality of healthcare delivered to dialysis-dependent patients and reduce cost.

Which Potentially Inappropriate Medications List Can Detect Patients At Risk of Readmissions in the Older Adult Population Admitted for Falls? An Observational Multicentre Study Using a Clinical Data Warehouse

BACKGROUND AND OBJECTIVE

Hospital readmissions are common in the older adult population and potentially inappropriate medications are known to be involved in these readmissions. Several lists of potentially inappropriate medications have been published in diverse countries in order to adapt the lists to local specificities. Among them, the Beers Criteria^® were first published in 1991 in the USA, followed by the French Laroche list, the Norwegian NORGEP criteria, the German PRISCUS list, the Austrian consensus panel list and the European list, EU-7. The main objective was to detect which potentially inappropriate medications list can better detect hospital readmissions within 30 days in the older adult population hospitalised for fall-related injuries.

METHODS

We conducted a multicentre, observational, retrospective cohort study. Data from older patients initially hospitalised for falls in 2019 and discharged home were retrieved from the Clinical Data Warehouse. Exposure to potentially inappropriate medications was classified according to the six lists mentioned above. The local ethics committee approved the study protocol (number CER-2020-79).

RESULTS

After adjustments using propensity score matching, taking a potentially inappropriate medication as per the Laroche and PRISCUS lists was associated with a 30-day hospital readmission with an odds ratio of 1.58 (95% confidence interval 1.06-2.37) and 1.68 (95% confidence interval 1.13-2.50), respectively, while the other four studied lists showed no associations with readmissions.

CONCLUSIONS

Our study evidenced that not all lists published allow the accurate prediction of hospital readmissions to the same extent. We found that the Laroche and PRISCUS lists were associated with increased 30-day all-cause hospital readmissions after an index admission with a fall-related injury.

Barriers and facilitators in using a Clinical Decision Support System for fall risk management for older people: a European survey

PURPOSE

Fall-Risk Increasing Drugs (FRIDs) are an important and modifiable fall-risk factor. A Clinical Decision Support System (CDSS) could support doctors in optimal FRIDs deprescribing. Understanding barriers and facilitators is important for a successful implementation of any CDSS. We conducted a European survey to assess barriers and facilitators to CDSS use and explored differences in their perceptions.

METHODS

We examined and compared the relative importance and the occurrence of regional differences of a literature-based list of barriers and facilitators for CDSS usage among physicians treating older fallers from 11 European countries.

RESULTS

We surveyed 581 physicians (mean age 44.9 years, 64.5% female, 71.3% geriatricians). The main barriers were technical issues (66%) and indicating a reason before overriding an alert (58%). The main facilitators were a CDSS that is beneficial for patient care (68%) and easy-to-use (64%). We identified regional differences, e.g., expense and legal issues were barriers for significantly more Eastern-European physicians compared to other regions, while training was selected less often as a facilitator by West-European physicians. Some physicians believed that due to the medical complexity of their patients, their own clinical judgement is better than advice from the CDSS.

CONCLUSION

When designing a CDSS for Geriatric Medicine, the patient's medical complexity must be addressed whilst maintaining the doctor's decision-making autonomy. For a successful CDSS implementation in Europe, regional differences in barrier perception should be overcome. Equipping a CDSS with prediction models has the potential to provide individualized recommendations for deprescribing FRIDs in older falls patients.

Polypharmacy Management in the Older Adults: A Scoping Review of Available Interventions

Background: Polypharmacy paves the way for non-adherence, adverse drug reactions, negative health outcomes, increased use of healthcare services and rising costs. Since it is most prevalent in the older adults, there is an urgent need for introducing effective strategies to prevent and manage the problem in this age group.

Purpose: To perform a scoping review critically analysing the available literature referring to the issue of polypharmacy management in the older adults and provide narrative summary.

Data sources: Articles published between January 2010–March 2018 indexed in CINHAL, EMBASE and PubMed addressing polypharmacy management in the older adults.

Results: Our search identified 49 papers. Among the identified interventions, the most often recommended ones involved various types of drug reviews based on either implicit or explicit criteria. Implicit criteria-based approaches are used infrequently due to their subjectivity, and limited implementability. Most of the publications advocate the use of explicit criteria, such as e.g. STOPP/START, Beers and Medication Appropriateness Index (MAI). However, their applicability is also limited due to long lists of potentially inappropriate medications covered. To overcome this obstacle, such instruments are often embedded in computerised clinical decision support systems.

Conclusion: Multiple approaches towards polypharmacy management are advised in current literature. They vary in terms of their complexity, applicability and usability, and no “gold standard” is identifiable. For practical reasons, explicit criteria-based drug reviews seem to be advisable. Having in mind that in general, polypharmacy management in the older adults is underused, both individual stakeholders, as well as policymakers should strengthen their efforts to promote these activities more strongly.

Health Impacts and Characteristics of Deprescribing Interventions in Older Adults: Protocol for a Systematic Review and Meta-analysis

Background

Deprescribing, a relatively recent concept, has been proposed as a promising solution to the growing issues of polypharmacy and use of medications of questionable benefit among older adults. However, little is known about the health outcomes of deprescribing interventions.

Objective

This paper presents the protocol of a study that aims to contribute to the knowledge on deprescribing by addressing two specific objectives: (1) describe the impact of deprescribing in adults ≥60 years on health outcomes or quality of life; and (2) determine the characteristics of effective interventions in deprescribing.

Methods

Primary studies targeting three concepts (older adults, deprescribing, and health or quality of life outcomes) will be included in the review. The search will be performed using key international databases (MEDLINE, EMBASE, CINAHL, Ageline, PsycInfo), and a special effort will be made to identify gray literature. Two reviewers will independently screen the articles, extract the information, and evaluate the quality of the selected studies. If methodologically feasible, meta-analyses will be performed for groups of intervention studies reporting on deprescribing interventions for similar medications, used for similar or identical indications, and reporting on similar outcomes (eg, benzodiazepines used against insomnia and studies reporting on quality of sleep or quality of life). Alternatively, the results will be presented in bottom-line statements (objective 1) and a matrix outlining effective interventions (objective 2).

Results

The knowledge synthesis may be limited by the availability of high-quality clinical trials on deprescribing and their outcomes in older adults. Additionally, analyses will likely be affected by studies on the deprescribing of different types of molecules within the same indication (eg, different pharmacological classes and medications to treat hypertension) and different measures of health and quality of life outcomes for the same indication. Nevertheless, we expect the review to identify which deprescribing interventions lead to improved health outcomes among seniors and which of their characteristics contribute to these outcomes.

Conclusions

This systematic review will contribute to a better understanding of the health outcomes of deprescribing interventions among seniors.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42015020866; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42015020866

International Registered Report Identifier (IRRID)

PRR1-10.2196/25200

Frequency and Acceptance of Clinical Decision Support System-Generated STOPP/START Signals for Hospitalised Older Patients with Polypharmacy and Multimorbidity

BACKGROUND

The Screening Tool of Older Persons' Prescriptions (STOPP)/Screening Tool to Alert to Right Treatment (START) instrument is used to evaluate the appropriateness of medication in older people. STOPP/START criteria have been converted into software algorithms and implemented in a clinical decision support system (CDSS) to facilitate their use in clinical practice.

OBJECTIVE

Our objective was to determine the frequency of CDSS-generated STOPP/START signals and their subsequent acceptance by a pharmacotherapy team in a hospital setting.

DESIGN AND METHODS

Hospitalised older patients with polypharmacy and multimorbidity allocated to the intervention arm of the OPERAM (OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly) trial underwent a CDSS-assisted structured medication review in four European hospitals. We evaluated the frequency of CDSS-generated STOPP/START signals and the subsequent acceptance of these signals by a trained pharmacotherapy team consisting of a physician and pharmacist after evaluation of clinical applicability to the individual patient, prior to discussing pharmacotherapy optimisation recommendations with the patient and attending physicians. Multivariate linear regression analysis was used to investigate potential patient-related (e.g. age, number of co-morbidities and medications) and setting-related (e.g. ward type, country of inclusion) determinants for acceptance of STOPP and START signals.

RESULTS

In 819/826 (99%) of the patients, at least one STOPP/START signal was generated using a set of 110 algorithms based on STOPP/START v2 criteria. Overall, 39% of the 5080 signals were accepted by the pharmacotherapy team. There was a high variability in the frequency and the subsequent acceptance of the individual STOPP/START criteria. The acceptance ranged from 2.5 to 75.8% for the top ten most frequently generated STOPP and START signals. The signal to stop a drug without a clinical indication was most frequently generated (28%), with more than half of the signals accepted (54%). No difference in mean acceptance of STOPP versus START signals was found. In multivariate analysis, most patient-related determinants did not predict acceptance, although the acceptance of START signals increased in patients with one or more hospital admissions (+ 7.9; 95% confidence interval [CI] 1.6-14.1) or one or more falls in the previous year (+ 7.1; 95% CI 0.7-13.4). A higher number of co-morbidities was associated with lower acceptance of STOPP (- 11.8%; 95% CI - 19.2 to - 4.5) and START (- 11.0%; 95% CI - 19.4 to - 2.6) signals for patients with more than nine and between seven and nine co-morbidities, respectively. For setting-related determinants, the acceptance differed significantly between the participating trial sites. Compared with Switzerland, the acceptance was higher in Ireland (STOPP: + 26.8%; 95% CI 16.8-36.7; START: + 31.1%; 95% CI 18.2-44.0) and in the Netherlands (STOPP: + 14.7%; 95% CI 7.8-21.7). Admission to a surgical ward was positively associated with acceptance of STOPP signals (+ 10.3%; 95% CI 3.8-16.8).

CONCLUSION

The involvement of an expert team in translating population-based CDSS signals to individual patients is essential, as more than half of the signals for potential overuse, underuse, and misuse were not deemed clinically appropriate in a hospital setting. Patient-related potential determinants were poor predictors of acceptance. Future research investigating factors that affect patients' and physicians' agreement with medication changes recommended by expert teams may provide further insight for implementation in clinical practice.

REGISTRATION

ClinicalTrials.gov Identifier: NCT02986425.

A Systematic Review of Interventions to Improve Analgesic Use and Appropriateness in Long-Term Care Facilities

OBJECTIVES

To systematically review the effectiveness of interventions to improve analgesic use and appropriateness in long-term care facilities (LTCFs).

DESIGN

Systematic review.

SETTING AND PARTICIPANTS

MEDLINE, Embase, PsycINFO, and CINAHL Plus were searched from inception to June 2021. Randomized controlled trials (RCTs), controlled and uncontrolled prospective interventions that included analgesic optimization, and reported postintervention change in analgesic use or appropriateness in LTCFs were included.

METHODS

Screening, data extraction, and quality assessment were performed independently by 2 review authors.

RESULTS

Eight cluster RCTs, 2 controlled, and 6 uncontrolled studies comprising 9056 residents across 9 countries were included. The 16 interventions included education (n = 13), decision support (n = 7), system modifications (n = 6), and/or medication review (n = 3). Six interventions changed analgesic use or appropriateness, all of which included prescribers, 5 involved multidisciplinary collaboration, and 5 included a component of education. Education alone changed analgesic use and appropriateness in 1 study. Decision support was effective when combined with education in 3 interventions. Overall, 13 studies reported analgesic optimization as part of pain management interventions and 3 studies focused on medication optimization. Two pain management interventions reduced the percentage of residents reporting pain not receiving analgesics by 50% to 60% (P = .03 and P < .001, respectively), and 1 improved analgesic appropriateness (P = .03). One reduced nonsteroidal anti-inflammatory drugs (NSAIDs) (P < .001) and another resulted in 3-fold higher odds of opioid prescription in advanced dementia [95% confidence interval (CI) 1.1-8.7]. One medication optimization intervention reduced NSAID prescription (P = .036), and another reduced as-needed opioid (95% CI 8.6-13.8) and NSAID prescription (95% CI 1.6-4.2).

CONCLUSIONS AND IMPLICATIONS

Interventions involving prescribers and enhanced roles for pharmacists and nurses, with a component of education, are most effective at changing analgesic use or appropriateness. Interventions combining education and decision support are also promising. Medication review interventions can change analgesic prescription, although there is currently minimal evidence in relation to possible corresponding improvements in resident-related outcomes.

Effectiveness of the application of an electronic medication management support system in patients with polypharmacy in general practice: a study protocol of cluster-randomised controlled trial (AdAM)

INTRODUCTION

Clinically complex patients often require multiple medications. Polypharmacy is associated with inappropriate prescriptions, which may lead to negative outcomes. Few effective tools are available to help physicians optimise patient medication. This study assesses whether an electronic medication management support system (eMMa) reduces hospitalisation and mortality and improves prescription quality/safety in patients with polypharmacy.

METHODS AND ANALYSIS

Planned design: pragmatic, parallel cluster-randomised controlled trial; general practices as randomisation unit; patients as analysis unit. As practice recruitment was poor, we included additional data to our primary endpoint analysis for practices and quarters from October 2017 to March 2021. Since randomisation was performed in waves, final study design corresponds to a stepped-wedge design with open cohort and step-length of one quarter.

SCOPE

general practices, Westphalia-Lippe (Germany), caring for BARMER health fund-covered patients.

POPULATION

patients (≥18 years) with polypharmacy (≥5 prescriptions).

SAMPLE SIZE

initially, 32 patients from each of 539 practices were required for each study arm (17 200 patients/arm), but only 688 practices were randomised after 2 years of recruitment. Design change ensures that 80% power is nonetheless achieved.

INTERVENTION

complex intervention eMMa.

FOLLOW-UP

at least five quarters/cluster (practice). recruitment: practices recruited/randomised at different times; after follow-up, control group practices may access eMMa.

OUTCOMES

primary endpoint is all-cause mortality and hospitalisation; secondary endpoints are number of potentially inappropriate medications, cause-specific hospitalisation preceded by high-risk prescribing and medication underuse.

STATISTICAL ANALYSIS

primary and secondary outcomes are measured quarterly at patient level. A generalised linear mixed-effect model and repeated patient measurements are used to consider patient clusters within practices. Time and intervention group are considered fixed factors; variation between practices and patients is fitted as random effects. Intention-to-treat principle is used to analyse primary and key secondary endpoints.

ETHICS AND DISSEMINATION

Trial approved by Ethics Commission of North-Rhine Medical Association. Results will be disseminated through workshops, peer-reviewed publications, local and international conferences.

TRIAL REGISTRATION

NCT03430336. ClinicalTrials.gov (https://clinicaltrials.gov/ct2/show/NCT03430336).

Elderly Patients in Primary Care are Still at Risks of Receiving Potentially Inappropriate Medications

Background

Most older adults with comorbidities in primary care clinics use multiple medications and are at risk of potentially inappropriate medications (PIMs) prescription.

Objective

This study examined the prevalence of polypharmacy and PIMs using Thai criteria for PIMs.

Methods

This study was a retrospective cross-sectional study. Data were collected from electronic medical records in a primary care clinic in 2018. Samples were patients aged ≥65 years old with at least 1 prescription. Variables included age, gender, comorbidities, and medications. The list of risk drugs for Thai elderly version 2 was the criteria for PIMs. The prevalence of polypharmacy and PIMs were calculated, and multiple logistic regression was conducted to examine associations between variables and PIMs.

Results

Of 2806 patients, 27.5% and 43.7% used ≥5 medications and PIMs, respectively. Of 10 290 prescriptions, 47% had at least 1 PIM. The top 3 PIMs were anticholinergics, proton-pump inhibitors, and nonsteroidal anti-inflammatory drugs (NSAIDs). Polypharmacy and dyspepsia were associated with PIM prescriptions (adjusted odds ratio 2.48 [95% confident interval or 95% CI 2.07-2.96] and 3.88 [95% CI 2.65-5.68], respectively).

Conclusion

Prescriptions with PIMs were high in the primary care clinic. Describing unnecessary medications is crucial to prevent negative health outcomes from PIMs. Computer-based clinical decision support, pharmacy-led interventions, and patient-specific drug recommendations are promising interventions to reduce PIMs in a primary care setting.

Potentially Inappropriate Medication Use in the Elderly

It is estimated that approximately half of adults, older than 65 years of age, have been prescribed potentially inappropriate medications (PIMs). This study's objective was to determine the prevalence of PIM use among older patients. Two retrospective chart reviews were performed on 200 and 164 older patients who underwent comprehensive geriatric assessments (CGAs) at outpatient geriatrics clinics at the Glenrose Rehabilitation Hospital (Glenrose) in 2012-13 and at the Misericordia Community Hospital (Misericordia) in 2016-17, respectively. Outcome measures included demographics; prevalence of PIM use; common PIMs used; whether PIM use was addressed, and if so, how; and total number of oral medications. At the Glenrose, the prevalence of PIM use was 45 per cent (90/200). Of the 90 patients who had used PIMs, 46.7 per cent (42/90) had at least one of their medications stopped or modified. At the Misericordia, the prevalence of PIM use was 57.3 per cent (94/164). Of the 94 patients who used PIMs, 47.9 per cent (45/94) had at least one of their medications stopped or modified. These results suggest that an increased awareness of PIM among physicians is needed to further decrease PIM use.

Potentially Inappropriate Medication Use in Older People: A Cross-sectional Study Using Beers Criteria

BACKGROUND

The use of Potentially Inappropriate Medications (PIMs) is common and negatively affects elderly health and disease prognosis.

OBJECTIVE

This study aims to analyze the frequency of PIMs in the elderly health records registered to a family health center and to identify risk factors, prescription/nonprescription distribution, distribution by healthcare institutions, number of doctors visits, and health literacy.

METHODS

In this cross-sectionalstudy, a stratified sampling method was used to select individuals aged ≥ 65 years. The health records of the participants up to the last 12 months were examined, and medicines used by participants were evaluated according to Beers 2019 criteria.

RESULTS

Most of the participants (89.7%, n:183) had PIMs in health records. The mean number of PIMs used by the elderly was 2.9±1.9(min:0, max:8). A positive linear relationship was observed between multimorbidity and the number of PIMs (p=0.001). There was no significant difference in terms of PIMs frequency among healthcare institutions. Prescription and nonprescription PIMs were found to belong to the same drug groups (Pain relievers and stomach medications). A linear and significant correlation was found between the number of PIMs and doctor visits (p=0.047).

CONCLUSION

The doctor should examine prescription and over-the-counter medications used by the elderly during the visit. It will be useful to establish a warning system stating that PIMs are available while registering the medications in the electronic system. So, it will be possible for health authorities to re-evaluate the treatment and replace PIMs with rational drug options.

Deprescribing in the Older Patient: A Narrative Review of Challenges and Solutions

Polypharmacy is a major challenge in healthcare for older people, and is associated with increased risks of adverse outcomes, such as delirium, falls, frailty, cognitive impairment and hospitalization. There is significant public and professional interest in the role of deprescribing in reducing medication-related harms in older people. We aim to provide a narrative review of 1) the safety and efficacy of deprescribing interventions, 2) the challenges and solutions of deprescribing research and implementation in clinical practice, and 3) the benefits of using Computerized Clinical Decision Support Systems (CCDSS) and Quality Indicators (QIs) in deprescribing research and practice. Deprescribing is an established management strategy to minimize polypharmacy and potentially inappropriate medications. There is limited clinical evidence for its efficacy on global and geriatric outcomes. Various challenges at patient, healthcare professional and healthcare system levels may impact on the success of deprescribing interventions in research and practice. Management strategies that target all levels of the healthcare system are required to overcome these challenges. Future studies may consider large multicenter prospective designs to establish the effects and sustainability of deprescribing interventions on clinical outcomes.

A Systematic Review of Potentially Inappropriate Medications Use and Related Costs Among the Elderly

OBJECTIVE

Potentially inappropriate medications (PIMs) use is a common phenomenon among older adults. This paper aimed to perform a systematic literature review to assess PIMs use and related costs among elderly persons.

METHODS

This study was a systematic review. PubMed, Scopus, and the Institute for Scientific Information engines were used to search for all relevant studies published until 2020. Studies were excluded if they did not estimate the cost of PIMs for the elderly. In addition, non-English articles, editorials, letters, and review articles were excluded. All eligible articles were assessed for methodological quality. Finally, we extracted general characteristics from each eligible study.

RESULTS

This study showed that the prevalence of PIMs use among older adults was more than 30%. Drugs related to the central nervous system and cardiovascular disease, benzodiazepines, analgesics, and nonsteroidal anti-inflammatory drugs were most commonly used as PIMs. These studies concluded that PIMs could impose a high economic burden on the elderly and society. The mean cost for older adults with PIMs use was almost USD$2000 more than the mean cost for older adults without PIMs. Additionally, the total cost of PIMs use for all elderly persons in Canada in 2013 was estimated at USD$419 million.

CONCLUSIONS

Focusing on the most common PIMs, such as benzodiazepines and nonsteroidal anti-inflammatory drugs, helps implementing cost-effective strategies for reducing PIMs use and decreasing their clinical and economic effects.

REview of potentially inappropriate MEDIcation pr[e]scribing in Seniors (REMEDI[e]S): French implicit and explicit criteria

PURPOSE

To establish a consensus on both explicit and implicit criteria in order to identify potentially inappropriate prescribing (PIP) in French older people aged 75 years and over or 65 years and over with multimorbidity.

METHODS

Fifteen experts in geriatrics, general practice, pharmacy, and clinical pharmacology were involved in a two-round Delphi survey to assess preliminary explicit and implicit criteria based on an extensive literature review and up-to-date evidence data. Experts were asked to rate their level of agreement using a 5-level Likert scale for inclusion of criteria and also for rationale and therapeutic alternatives. A consensus was considered as reached if at least 75% of the experts rated criteria as "strongly agreed" or "agreed."

RESULTS

The new tool included a seven-step algorithm (implicit criteria) encompassing the three main domains that define PIP (i.e. overprescribing, underprescribing, and misprescribing) and 104 explicit criteria. Explicit criteria were divided into 6 tables related to inappropriate drug duplications (n = 7 criteria), omissions of medications and/or medication associations (n = 16), medications with an unfavourable benefit/risk ratio and/or a questionable efficacy (n = 39), medications with an unsuitable dose (n = 4) or duration (n = 6), drug-disease (n = 13), and drug-drug interactions (n = 19).

CONCLUSION

The REMEDI[e]S tool (REview of potentially inappropriate MEDIcation pr[e]scribing in Seniors) is an original mixed tool, adapted to French medical practices, aimed at preventing PIP both at the individual level in clinical practice and the population level in large-scale studies. Therefore, its use could contribute to an improvement in healthcare professionals' prescribing practices and safer care in older adults.

Polypharmacy in Multiple Sclerosis: Current Knowledge and Future Directions

Polypharmacy, or the daily use of five or more medications, is well documented in older adults and linked to negative outcomes such as medication errors, adverse drug reactions, and increased healthcare utilization. Like older adults, people with multiple sclerosis (PwMS) are susceptible to polypharmacy, owing to the variety of treatments used to address individual multiple sclerosis (MS) symptoms and other comorbidities. Between 15-65% of PwMS meet criteria for polypharmacy; in this population, polypharmacy is associated with increased reports of fatigue, subjective cognitive impairment, and reduced quality of life. Despite evidence of adverse outcomes, polypharmacy among PwMS remains a neglected area of research. This article examines the current literature regarding polypharmacy in MS, as well as implications for clinical practice and directions for future research.

Multicomponent behavioral intervention to reduce exposure to anticholinergics in primary care older adults

OBJECTIVE

To test the impact of a multicomponent behavioral intervention to reduce the use of high-risk anticholinergic medications in primary care older adults.

DESIGN

Cluster-randomized controlled trial.

SETTING AND PARTICIPANTS

Ten primary care clinics within Eskenazi Health in Indianapolis.

INTERVENTION

The multicomponent intervention included provider- and patient-focused components. The provider-focused component was computerized decision support alerting of the presence of a high-risk anticholinergic and offering dose- and indication-specific alternatives. The patient-focused component was a story-based video providing education and modeling an interaction with a healthcare provider resulting in a medication change. Alerts within the medical record triggered staff to play the video for a patient. Our design intended for parallel, independent priming of both providers and patients immediately before an outpatient face-to-face interaction.

MEASUREMENT

Medication orders were extracted from the electronic medical record system to evaluate the prescribing behavior and population prevalence of anticholinergic users. The intervention was introduced April 1, 2019, through March 31, 2020, and a preintervention observational period of April 1, 2018, through March 31, 2019, facilitated difference in difference comparisons.

RESULTS

A total of 552 older adults had visits at primary care sites during the study period, with mean age of 72.1 (SD 6.4) years and 45.3% African American. Of the 259 provider-focused alerts, only three (1.2%) led to a medication change. Of the 276 staff alerts, 4.7% were confirmed to activate the patient-focused intervention. The intervention resulted in no significant differences in either the number of discontinue orders for anticholinergics (intervention: two additional orders; control: five fewer orders, p = 0.7334) or proportion of the population using anticholinergics following the intervention (preintervention: 6.2% and postintervention: 5.1%, p = 0.6326).

CONCLUSION

This multicomponent intervention did not reduce the use of high-risk anticholinergics in older adults receiving primary care. Improving nudges or a policy-focused component may be necessary to reduce use of high-risk medications.

Use of machine learning to predict clinical decision support compliance, reduce alert burden, and evaluate duplicate laboratory test ordering alerts

Objectives

While well-designed clinical decision support (CDS) alerts can improve patient care, utilization management, and population health, excessive alerting may be counterproductive, leading to clinician burden and alert fatigue. We sought to develop machine learning models to predict whether a clinician will accept the advice provided by a CDS alert. Such models could reduce alert burden by targeting CDS alerts to specific cases where they are most likely to be effective.

Materials and Methods

We focused on a set of laboratory test ordering alerts, deployed at 8 hospitals within the Partners Healthcare System. The alerts notified clinicians of duplicate laboratory test orders and advised discontinuation. We captured key attributes surrounding 60 399 alert firings, including clinician and patient variables, and whether the clinician complied with the alert. Using these data, we developed logistic regression models to predict alert compliance.

Results

We identified key factors that predicted alert compliance; for example, clinicians were less likely to comply with duplicate test alerts triggered in patients with a prior abnormal result for the test or in the context of a nonvisit-based encounter (eg, phone call). Likewise, differences in practice patterns between clinicians appeared to impact alert compliance. Our best-performing predictive model achieved an area under the receiver operating characteristic curve (AUC) of 0.82. Incorporating this model into the alerting logic could have averted more than 1900 alerts at a cost of fewer than 200 additional duplicate tests.

Conclusions

Deploying predictive models to target CDS alerts may substantially reduce clinician alert burden while maintaining most or all the CDS benefit.

Drug-Drug Interactions and Prescription Appropriateness at Hospital Discharge: Experience with COVID-19 Patients

BACKGROUND

Patients with coronavirus disease 2019 (COVID-19) are often elderly, with comorbidities, and receiving polypharmacy, all of which are known factors for potentially severe drug-drug interactions (DDIs) and the prescription of potentially inappropriate medications (PIMs).

OBJECTIVE

The aim of this study was to assess the risk of DDIs and PIMs in COVID-19 patients at hospital discharge.

METHOD

Patients with a proven diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection who were hospitalized between 21 February and 30 April 2020, treated with at least two drugs, and with available information regarding pharmacological treatments upon admission and at discharge were considered. The appropriateness of drug prescriptions was assessed using INTERcheck^®.

RESULTS

A significant increase in the prescription of proton pump inhibitors and heparins was found when comparing admission with hospital discharge (from 24 to 33% [p < 0.05] and from 1 to 17% [p < 0.01], respectively). The increased prescription of heparins at discharge resulted in a highly significant increase in the potentially severe DDIs mediated by this class of drugs. 51% of COVID-19 patients aged > 65 years had at least one PIM upon admission, with an insignificant increment at discharge (58%).

CONCLUSION

An increased number of prescribed drugs was observed in COVID-19 patients discharged from our hospital. The addition of heparins is appropriate according to the current literature, while the use of proton pump inhibitors is more controversial. Particular attention should be paid to the risk of bleeding complications linked to heparin-based DDIs.

Impact of a C. difficile infection (CDI) reduction bundle and its components on CDI diagnosis and prevention

BACKGROUND

Published bundles to reduce Clostridioides difficile Infection (CDI) frequently lack information on compliance with individual elements. We piloted a computerized clinical decision support-based intervention bundle and conducted detailed evaluation of several intervention-related measures.

METHODS

A quasi-experimental study of a bundled intervention was performed at 2 acute care community hospitals in Maryland. The bundle had five components: (1) timely placement in enteric precautions, (2) appropriate CDI testing, (3) reducing proton-pump inhibitor (PPI) use, (4) reducing high-CDI risk antibiotic use, and (5) optimizing use of a sporicidal agent for environmental cleaning. Chi-square and Kruskal-Wallis tests were used to compare measure differences. An interrupted time series analysis was used to evaluate impact on hospital-onset (HO)-CDI.

RESULTS

Placement of CDI suspects in enteric precautions before test results did not change. Only hospital B decreased the frequency of CDI testing and reduced inappropriate testing related to laxative use. Both hospitals reduced the use of PPI and high-risk antibiotics. A 75% decrease in HO-CDI immediately postimplementation was observed for hospital B only.

CONCLUSION

A CDI reduction bundle showed variable impact on relevant measures. Hospital-specific differential uptake of bundle elements may explain differences in effectiveness, and emphasizes the importance of measuring processes and intermediate outcomes.

Potentially Inappropriate Medication Use and Hard Braking Events in Older Drivers

Potentially inappropriate medications (PIMs) identified by the American Geriatrics Society should generally be avoided by older adults because of ineffectiveness or excess risk of adverse effects. Few studies have examined the effects of PIMs on driving safety measured by prospectively and objectively collected driving data. Data for this study came from the Longitudinal Research on Aging Drivers study, a multisite naturalistic driving study of older adults. Multivariable negative binominal modeling was used to estimate incidence rate ratios and 95% confidence intervals of hard braking events (proxies for unsafe driving behavior defined as events with a deceleration rate ≥0.4 g) associated with PIM use among older drivers. The study sample consisted of 2932 drivers aged 65-79 years at baseline, including 542 (18.5%) who used at least one PIM. These drivers were followed through an in-vehicle recording device for up to 44 months. The overall incidence of hard braking events was 1.16 per 1000 miles. Use of PIMs was associated with a 10% increased risk of hard braking events. Compared to drivers who were not using PIMs, the risk of hard braking events increased 6% for those using one PIM, and 24% for those using two or more PIMs. Use of PIMs by older adult drivers is associated in a dose-response fashion with elevated risks of hard braking events. Reducing PIM use in older adults might help improve driving safety as well as health outcomes.

Nobody ever questions-Polypharmacy in care homes: A mixed methods evaluation of a multidisciplinary medicines optimisation initiative

BACKGROUND

Nurse-led monitoring of patients for signs and symptoms associated with documented 'undesirable effects' of medicines has potential to prevent avoidable harm, and optimise prescribing.

INTERVENTION

The Adverse Drug Reaction Profile for polypharmacy (ADRe-p) identifies and documents putative adverse effects of medicines commonly prescribed in primary care. Nurses address some problems, before passing ADRe-p to pharmacists and prescribers for review, in conjunction with prescriptions.

OBJECTIVES

We investigated changes in: the number and nature of residents' problems as recorded on ADRe-p; prescription regimens; medicines optimisation: and healthcare costs. We explored aetiologies of problems identified and stakeholders' perspectives.

SETTING AND PARTICIPANTS

In three UK care homes, 19 residents completed the study, December 2018 to May 2019. Two service users, three pharmacists, six nurses gave interviews.

METHODS

This mixed-method process evaluation integrated data from residents' ADRe-ps and medicines charts, at the study's start and 5-10 weeks later.

RESULTS

We recruited three of 27 homes approached and 26 of 45 eligible residents; 19 completed ADRe-p at least twice. Clinical gains were identified for 17/19 residents (mean number of symptoms 3 SD 1.67, range 0-7). Examples included management of: pain (six residents), seizures (three), dyspnoea (one), diarrhoea (laxatives reduced, two), falls (two of five able to stand). One or more medicine was de-prescribed or dose reduced for 12/19 residents. ADRe administration and review cost ~£30 in staff time. ADRe-p helped carers and nurses bring residents' problems to the attention of prescribers.

IMPLICATIONS

ADRe-p relieved unnecessary suffering. It supported carers and nurses by providing a tool to engage with pharmacists and prescribers, and was the only observable strategy for multidisciplinary team working around medicines optimisation. ADRe-p improved care by: a) regular systematic checks and problem documentation; b) information transfer from care home staff to prescribers and pharmacists; c) recording changes.

REGISTRATION

NLM Identifier NCT03955133; ClinicalTrials.gov.

Machine Learning Approach to Reduce Alert Fatigue Using a Disease Medication-Related Clinical Decision Support System: Model Development and Validation

Background

Computerized physician order entry (CPOE) systems are incorporated into clinical decision support systems (CDSSs) to reduce medication errors and improve patient safety. Automatic alerts generated from CDSSs can directly assist physicians in making useful clinical decisions and can help shape prescribing behavior. Multiple studies reported that approximately 90%-96% of alerts are overridden by physicians, which raises questions about the effectiveness of CDSSs. There is intense interest in developing sophisticated methods to combat alert fatigue, but there is no consensus on the optimal approaches so far.

Objective

Our objective was to develop machine learning prediction models to predict physicians’ responses in order to reduce alert fatigue from disease medication–related CDSSs.

Methods

We collected data from a disease medication–related CDSS from a university teaching hospital in Taiwan. We considered prescriptions that triggered alerts in the CDSS between August 2018 and May 2019. Machine learning models, such as artificial neural network (ANN), random forest (RF), naïve Bayes (NB), gradient boosting (GB), and support vector machine (SVM), were used to develop prediction models. The data were randomly split into training (80%) and testing (20%) datasets.

Results

A total of 6453 prescriptions were used in our model. The ANN machine learning prediction model demonstrated excellent discrimination (area under the receiver operating characteristic curve [AUROC] 0.94; accuracy 0.85), whereas the RF, NB, GB, and SVM models had AUROCs of 0.93, 0.91, 0.91, and 0.80, respectively. The sensitivity and specificity of the ANN model were 0.87 and 0.83, respectively.

Conclusions

In this study, ANN showed substantially better performance in predicting individual physician responses to an alert from a disease medication–related CDSS, as compared to the other models. To our knowledge, this is the first study to use machine learning models to predict physician responses to alerts; furthermore, it can help to develop sophisticated CDSSs in real-world clinical settings.

Drug-Drug Interactions and Prescription Appropriateness in Patients with COVID-19: A Retrospective Analysis from a Reference Hospital in Northern Italy

Background

Patients hospitalised with severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2; coronavirus 2019 disease (COVID-19)] infection are frequently older with co-morbidities and receiving polypharmacy, all of which are known risk factors for drug–drug interactions (DDIs). The pharmacological burden may be further aggravated by the addition of treatments for COVID-19.

Objective

The aim of this study was to assess the risk of potential DDIs upon admission and during hospitalisation in patients with COVID-19 treated at our hospital.

Methods

We retrospectively analysed 502 patients with COVID-19 (mean age 61 ± 16 years, range 15–99) treated at our hospital with a proven diagnosis of SARS-CoV-2 infection hospitalised between 21 February and 30 April 2020 and treated with at least two drugs.

Results

Overall, 68% of our patients with COVID-19 were exposed to at least one potential DDI, and 55% were exposed to at least one potentially severe DDI. The proportion of patients experiencing potentially severe DDIs increased from 22% upon admission to 80% during hospitalisation. Furosemide, amiodarone and quetiapine were the main drivers of potentially severe DDIs upon admission, and hydroxychloroquine and particularly lopinavir/ritonavir were the main drivers during hospitalisation. The majority of potentially severe DDIs carried an increased risk of cardiotoxicity. No potentially severe DDIs were identified in relation to tocilizumab and remdesivir.

Conclusions

Among hospitalised patients with COVID-19, concomitant treatment with lopinavir/ritonavir and hydroxychloroquine led to a dramatic increase in the number of potentially severe DDIs. Given the high risk of cardiotoxicity and the scant and conflicting data concerning their efficacy in treating SARS-CoV-2 infection, the use of lopinavir/ritonavir and hydroxychloroquine in patients with COVID-19 with polypharmacy needs to be carefully considered.

Discontinuation of Statins in Veterans Admitted to Nursing Homes near the End of Life

BACKGROUND/OBJECTIVES

Geriatric guidelines recommend against statin use in older adults with limited life expectancy (LLE) or advanced dementia (AD). This study examined resident and facility factors predicting statin discontinuation after nursing home (NH) admission in veterans with LLE/AD taking statins for secondary prevention.

DESIGN

Retrospective cohort study of Veterans Affairs (VA) bar code medication administration records, Minimum Data Set (MDS) assessments, and utilization records linked to Medicare claims.

SETTING

VA NHs, known as community living centers (CLCs).

PARTICIPANTS

Veterans aged 65 and older with coronary artery disease, stroke, or diabetes mellitus, type II, admitted in fiscal years 2009 to 2015, who met criteria for LLE/AD on their admission MDS and received statins in the week after admission (n = 13,110).

MEASUREMENTS

Residents were followed until statin discontinuation (ie, gap in statin use ≥14 days), death, or censoring due to discharge, day 91 of the stay, or end of the study period. Competing risk models assessed cumulative incidence and predictors of discontinuation, stratified by whether the resident had their end-of-life (EOL) status designated or used hospice at admission.

RESULTS

Overall cumulative incidence of statin discontinuation was 31% (95% confidence interval [CI] = 30%-32%) by day 91, and it was markedly higher in those with (52%; 95% CI = 50%-55%) vs without (25%; 95% CI = 24%-26%) EOL designation/hospice. In patients with EOL designation/hospice (n = 2,374), obesity, congestive heart failure, and admission from nonhospital settings predicted decreased likelihood of discontinuation; AD, dependency in activities of daily living, greater number of medications, and geographic region predicted increased likelihood of discontinuation. In patients without EOL designation/hospice (n = 10,736), older age and several specific markers of poor prognosis predicted greater discontinuation, whereas obesity/overweight predicted decreased discontinuation.

CONCLUSION

Most veterans with LLE/AD taking statins for secondary prevention do not discontinue statins following CLC admission. Designating residents as EOL status, hospice use, and individual clinical factors indicating poor prognosis may prompt deprescribing.

Evaluating the Impact of the Grading and Assessment of Predictive Tools Framework on Clinicians and Health Care Professionals' Decisions in Selecting Clinical Predictive Tools: Randomized Controlled Trial

BACKGROUND

While selecting predictive tools for implementation in clinical practice or for recommendation in clinical guidelines, clinicians and health care professionals are challenged with an overwhelming number of tools. Many of these tools have never been implemented or evaluated for comparative effectiveness. To overcome this challenge, the authors developed and validated an evidence-based framework for grading and assessment of predictive tools (the GRASP framework). This framework was based on the critical appraisal of the published evidence on such tools.

OBJECTIVE

The aim of the study was to examine the impact of using the GRASP framework on clinicians' and health care professionals' decisions in selecting clinical predictive tools.

METHODS

A controlled experiment was conducted through a web-based survey. Participants were randomized to either review the derivation publications, such as studies describing the development of the predictive tools, on common traumatic brain injury predictive tools (control group) or to review an evidence-based summary, where each tool had been graded and assessed using the GRASP framework (intervention group). Participants in both groups were asked to select the best tool based on the greatest validation or implementation. A wide group of international clinicians and health care professionals were invited to participate in the survey. Task completion time, rate of correct decisions, rate of objective versus subjective decisions, and level of decisional conflict were measured.

RESULTS

We received a total of 194 valid responses. In comparison with not using GRASP, using the framework significantly increased correct decisions by 64%, from 53.7% to 88.1% (88.1/53.7=1.64; t₁₉₃=8.53; P<.001); increased objective decision making by 32%, from 62% (3.11/5) to 82% (4.10/5; t₁₈₉=9.24; P<.001); decreased subjective decision making based on guessing by 20%, from 49% (2.48/5) to 39% (1.98/5; t₁₈₈=-5.47; P<.001); and decreased prior knowledge or experience by 8%, from 71% (3.55/5) to 65% (3.27/5; t₁₈₇=-2.99; P=.003). Using GRASP significantly decreased decisional conflict and increased the confidence and satisfaction of participants with their decisions by 11%, from 71% (3.55/5) to 79% (3.96/5; t₁₈₈=4.27; P<.001), and by 13%, from 70% (3.54/5) to 79% (3.99/5; t₁₈₈=4.89; P<.001), respectively. Using GRASP decreased the task completion time, on the 90th percentile, by 52%, from 12.4 to 6.4 min (t₁₉₃=-0.87; P=.38). The average System Usability Scale of the GRASP framework was very good: 72.5% and 88% (108/122) of the participants found the GRASP useful.

CONCLUSIONS

Using GRASP has positively supported and significantly improved evidence-based decision making. It has increased the accuracy and efficiency of selecting predictive tools. GRASP is not meant to be prescriptive; it represents a high-level approach and an effective, evidence-based, and comprehensive yet simple and feasible method to evaluate, compare, and select clinical predictive tools.

An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study

Background

People with low back pain (LBP) in the community often do not receive evidence-based advice and management. Community pharmacists can play an important role in supporting people with LBP as pharmacists are easily accessible to provide first-line care. However, previous research suggests that pharmacists may not consistently deliver advice that is concordant with guideline recommendations and may demonstrate difficulty determining which patients require prompt medical review. A clinical decision support system (CDSS) may enhance first-line care of LBP, but none exists to support the community pharmacist–client consultation.

Objective

This study aimed to develop a CDSS to guide first-line care of LBP in the community pharmacy setting and to evaluate the pharmacist-reported usability and acceptance of the prototype system.

Methods

A cross-platform Web app for the Apple iPad was developed in conjunction with academic and clinical experts using an iterative user-centered design process during interface design, clinical reasoning, program development, and evaluation. The CDSS was evaluated via one-to-one user-testing with 5 community pharmacists (5 case vignettes each). Data were collected via video recording, screen capture, survey instrument (system usability scale), and direct observation.

Results

Pharmacists’ agreement with CDSS-generated self-care recommendations was 90% (18/20), with medicines recommendations was 100% (25/25), and with referral advice was 88% (22/25; total 70 recommendations). Pharmacists expressed uncertainty when screening for serious pathology in 40% (10/25) of cases. Pharmacists requested more direction from the CDSS in relation to automated prompts for user input and page navigation. Overall system usability was rated as excellent (mean score 92/100, SD 6.5; 90th percentile compared with similar systems), with acceptance rated as good to excellent.

Conclusions

A novel CDSS (high-fidelity prototype) to enhance pharmacist care of LBP was developed, underpinned by clinical practice guidelines and informed by a multidisciplinary team of experts. User-testing revealed a high level of usability and acceptance of the prototype system, with suggestions to improve interface prompts and information delivery. The small study sample limits the generalizability of the findings but offers important insights to inform the next stage of system development.

Reducing medicine-induced deterioration and adverse reactions (ReMInDAR) trial: study protocol for a randomised controlled trial in residential aged-care facilities assessing frailty as the primary outcome

INTRODUCTION

Many medicines have adverse effects which are difficult to detect and frequently go unrecognised. Pharmacist monitoring of changes in signs and symptoms of these adverse effects, which we describe as medicine-induced deterioration, may reduce the risk of developing frailty. The aim of this trial is to determine the effectiveness of a 12-month pharmacist service compared with usual care in reducing medicine-induced deterioration, frailty and adverse reactions in older people living in aged-care facilities in Australia.

METHODS AND ANALYSIS

The reducing medicine-induced deterioration and adverse reactions trial is a multicentre, open-label randomised controlled trial. Participants will be recruited from 39 facilities in South Australia and Tasmania. Residents will be included if they are using four or more medicines at the time of recruitment, or taking more than one medicine with anticholinergic or sedative properties. The intervention group will receive a pharmacist assessment which occurs every 8 weeks. The pharmacists will liaise with the participants' general practitioners when medicine-induced deterioration is evident or adverse events are considered serious. The primary outcome is a reduction in medicine-induced deterioration from baseline to 6 and 12 months, as measured by change in frailty index. The secondary outcomes are changes in cognition scores, 24-hour movement behaviour, grip strength, weight, percentage robust, pre-frail and frail classification, rate of adverse medicine events, health-related quality of life and health resource use. The statistical analysis will use mixed-models adjusted for baseline to account for repeated outcome measures. A health economic evaluation will be conducted following trial completion using data collected during the trial.

ETHICS AND DISSEMINATION

Ethics approvals have been obtained from the Human Research Ethics Committee of University of South Australia (ID:0000036440) and University of Tasmania (ID:H0017022). A copy of the final report will be provided to the Australian Government Department of Health.

TRIAL REGISTRATION NUMBER

Australian and New Zealand Trials Registry ACTRN12618000766213.